Feasibility Pump Algorithm for Sparse Representation under Laplacian Noise

Table 1

Mean relative errors (11) for SFP (top in each cell), SFPreg (middle), and RLAD (bottom) for matrix conditioning of 1000.

	5	7	9	11
SNR = 10	0.262	0.379	0.427	0.471
	0.255	0.255	0.248	0.241
	0.447	0.450	0.500	0.471
SNR = 20	0.084	0.143	0.378	0.338
	0.084	0.084	0.082	0.082
	0.201	0.276	0.410	0.415
SNR = 30	0.027	0.027	0.095	0.157
	0.027	0.026	0.025	0.025
	0.068	0.231	0.270	0.464
SNR =